Evaluation of air quality zone classification methods based on ambient air concentration exposure

Abstract

A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.

Forecasting air quality time series using deep learning

“…The land-sea breezes continuously shift direction and speed over the course of the day, recirculating pollution back and forth from land sources creating different zones of concentration mixing (Freeman et al, 2017a). Fixed air monitoring stations are operated throughout the country near residential and industrial areas, but predominantly in the coastal zone areas (Freeman et al, 2017b). For this study, data were collected using OPSIS differential optical absorption spectroscopy (DOAS) analyzers (www.opsis.se) located near a local college, as shown in Figure 6.…”

Optimizing best management practices to control anthropogenic sources of atmospheric phosphorus deposition to inland lakes

“…Dust emissions from paved roads are also a function of the volume of vehicular traffic on the road (Freeman et al 2015a;2015b;2017a;2017b). Dust can be generated and emitted from combustion by-products, released through the tailpipe of the car, dust from the application of brake pads, and the resuspension of dust from other sources that deposited on the road and are not resuspended by the disturbance.…”